Martin Lillholm
Professor
Machine Learning
Universitetsparken 1
2100 København Ø
ORCID: 0000-0002-1402-6899
1 - 1 ud af 1Pr. side: 10
- 2022
- Udgivet
Robust Cross-vendor Mammographic Texture Models Using Augmentation-based Domain Adaptation for Long-term Breast Cancer Risk
Lauritzen, Andreas, von Euler-Chelpin, My Catarina, Lynge, Elsebeth, Vejborg, I. M. M., Nielsen, Mads, Karssemeijer, N. & Lillholm, Martin, 2022, arXiv.org, 30 s.Publikation: Working paper › Preprint › Forskning
ID: 152298477
Flest downloads
-
1595
downloads
Mammographic texture resemblance generalizes as an independent risk factor for breast cancer
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › fagfællebedømt
Udgivet -
594
downloads
Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › fagfællebedømt
Udgivet -
319
downloads
Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › fagfællebedømt
Udgivet